31:17

Machine Learning Malayalam: Decision Tree Types & ID3 Algorithm Made Easy(മലയാളത്തിൽ)

20:43

Linear Discriminant Analysis (LDA) for Classification and Dimensionality Reduction | Malayalam

14:49

Singular Value Decomposition (SVD) for Dimensionality Reduction | Malayalam(മലയാളത്തിൽ)

21:25

Singular Value Decomposition (SVD) Explained with Example | Malayalam Machine Learning Tutorial

16:42

R 6.1 -Skewness and Kurtosis Explained with Example in R | Malayalam Tutorial (മലയാളത്തിൽ)

25:16

K-Medoids Clustering Algorithm Explained with Example | Malayalam Machine Learning Tutorial

08:42

Principal Component Analysis (PCA) – Part 2 with Example | Malayalam Machine Learning Tutorial|

24:04

Logistic Regression Algorithm Explained with Example|Malayalam Machine Learning Tutorial| മലയാളത്തിൽ

23:40

Logistic Regression with Sigmoid Function Derivation | Malayalam Machine Learning Tutorial

20:53

Linear SVM – Hyperplane Calculation with Example | Machine Learning Tutorial in Malayalam

25:42

Linear SVM – Hyperplane Calculation Explained | Malayalam Machine Learning Tutorial(മലയാളത്തിൽ)

12:00

Support Vector Machine (SVM) Algorithm Explained | Malayalam Machine Learning Tutorial (മലയാളത്തിൽ)

15:48

Naive Bayes Algorithm with Multiple Predictors | Malayalam Machine Learning Tutorial

10:21

Naive Bayes Algorithm Explained with Example | Malayalam Machine Learning Tutorial(മലയാളത്തിൽ)

18:59

CC1 CL6-Understanding Eucalyptus Cloud Computing Architecture | Eucalyptus Fundamentals (മലയാളത്തിൽ)

25:11

CC1 CL5-Cloud Computing: Virtualization Techniques - Full, Para, Hybrid, OS-level (മലയാളത്തിൽ)

07:36

CC1 CL4-CLOUD COMPUTING - Virtualization Architectures: Bare-metal vs Hosted Hypervisor (മലയാളത്തിൽ)

13:20

R TUTORIAL 16:One-Way MANOVA in R using manova() Function | Explained with Example (മലയാളത്തിൽ)

19:20

R TUTORIAL 15-Two-Way ANOVA Test in R with Example | Using aov() Function (മലയാളത്തിൽ)(മലയാളത്തിൽ)

26:01

R TUTORIAL 14-One-Way ANOVA Test in R with Example | Using aov() Function (മലയാളത്തിൽ)

17:45

R TUTORIAL 13 -. T-Test in R using t.test() Function | Explained with Examples (മലയാളത്തിൽ)

27:20

R TUTORIAL 12-Z-Test in R using z.test() – Part 2 | Two-Sample Test & Real Example (മലയാളത്തിൽ)

05:46

R TUTORIAL 11-Chi-Square Test in R using chisq.test() Function | Explained with Example (മലയാളത്തിൽ)

09:37

R TUTORIAL 10-ANOVA Test in R using aov() Function | Statistical Inference Explained (മലയാളത്തിൽ)

10:47

R TUTORIAL 9-: Z-Test Using z.test() Function | Statistical Inference in R (മലയാളത്തിൽ)

26:02

R Tutorial 8: T-Test Explained using t.test() Function | Statistical Inference in R (മലയാളത്തിൽ)

06:42

R 7 -Random Sampling in R – With & Without Replacement | Malayalam Tutorial(മലയാളത്തിൽ)

08:08

R 6-Descriptive Statistics in R | Summary, Mean, Median, Mode, SD, Variance | Tutorial (മലയാളത്തിൽ)

10:06

R 5-Graphics in R – Stem & Leaf, P-P Plot, Q-Q Plot Explained | Malayalam Tutorial (മലയാളത്തിൽ)

13:42

JAVA SWING- Overview,Hierarchy,swing classes,feactures (മലയാളം)

12:31

JAVA AWT- Abstract window toolkit (Explained with java program) (മലയാളം)

19:54

JAVA EVENT HANDLING- (Explained with java program) (മലയാളം)

05:44

R 4-Learn Loops and Conditions in R (if, for, while, switch) – Malayalam Tutorial(മലയാളത്തിൽ)

13:07

R 3-Learn R Built-in Functions – Math & String | Malayalam Tutorial(മലയാളത്തിൽ)

11:09

R 2-R Programming Tutorial – Barplot, Scatter, Line, Histogram & Boxplot Explained | (മലയാളത്തിൽ)

20:01

R 1-Learn R Programming – Input & Indexing Concepts (Malayalam Tutorial)(മലയാളത്തിൽ)

06:25

R PROGRAMMING LANGUAGE -Inputing methods in R programming language(മലയാളത്തിൽ)

20:59

Principal Component Analysis (PCA) Explained with Example – Part 1|Malayalam ML Tutorial| മലയാളത്തിൽ

15:46

Random Forest Algorithm Explained with Example | Malayalam Machine Learning Tutorial|മലയാളത്തിൽ

17:33

Decision Tree Classification Algorithm with Example | Malayalam Machine Learning Tutorial|മലയാളത്തിൽ

15:30

K-Means Clustering Algorithm Explained with Example|Malayalam Machine Learning Tutorial| മലയാളത്തിൽ

18:40

JAVA RMI-Remote method Invocation (Explained with java program) (മലയാളം)

05:24

DATA MINING-BINNING METHODS Data cleaning METHOD (മലയാളത്തിൽ)

18:05

K-Nearest Neighbour (KNN) Algorithm Explained with Example | Malayalam Machine Learning Tutorial

07:45

DATA MINING-DATA REDUCTION- WAVELET TRANSFORM-dimensionality METHOD (മലയാളത്തിൽ)

15:39

CC1 CL3-Cloud Computing: Implementation Levels of Virtualization (മലയാളത്തിൽ)

14:32

CC1 CL2-CLOUD COMPUTING -Virtual machines & virtualization middleware- HYPERVISOR (മലയാളത്തിൽ)

17:08

CC1CL1-Cloud Computing Concepts & Difference Between Cloud and Grid Computing (മലയാളത്തിൽ)

06:12

DM1 CL5-OLAP OPERATIONS Roll up Drill Down, Slice & Dice Pivot(IN ENGLISH)

05:56

DM1 CL4-OLAP (Online Analytical processing) OLAP vs OLTP (IN ENGLISH)

07:48

DM1 CL3-SCHEMAS IN DATA WAREHOUSE STAR, SNOWFLAKE AND FACT CONSTELLATION (IN ENGLISH)

10:52

DM1 CL2-MULTIDIMENSIONAL MODEL IN DATA WAREHOUSE fact &dimensions, data cubes,4-D cuboid(IN ENGLISH)

09:32

DM1CL1- DATA MINING-DATA WAREHOUSE Characteristics and functions(IN ENGLISH)

21:48

DM4 CL4-Density-Based Clustering - DBSCAN, HDBSCAN & OPTICS Explained (മലയാളത്തിൽ)

11:19

DM4 CL5- Outlier Analysis - Types: Global and Collective Conditions (Data Mining Malayalam)

11:11

DM4 CL3-K-means Clustering - Partitioning Method Explained (മലയാളത്തിൽ)

13:00

DM4 CL2-Different Methods of Cluster Analysis in Data Mining (Malayalam)

10:16

DM4 CL1-Cluster Analysis - Definition, Concept, and Properties Explained (മലയാളത്തിൽ)

07:13

DM3 CL9-Prediction Methods - Linear, Nonlinear, and Logistic Regression Explained (മലയാളത്തിൽ)

17:45

DM3 CL8-Lazy Learners- K-Nearest Neighbour (KNN) & Case-Based Reasoning (CBR) Explained (മലയാളത്തിൽ)